The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Organ Recognition in Ultrasound images Using Log Power Spectrum

로그 전력 스펙트럼을 이용한 초음파 영상에서의 장기인식

  • 박수진 (LG전자 시스템IC R&D 센터) ;
  • 손재곤 (삼성전자 무선사업부) ;
  • 김남철 (경북대학교 전자전기공학부)
  • Published : 2003.09.01
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Abstract

In this paper, we propose an algorithm for organ recognition in ultrasound images using log power spectrum. The main procedure of the algorithm consists of feature extraction and feature classification. In the feature extraction, as a translation invariant feature, log power spectrum is used for extracting the information on echo of the organs tissue from a preprocessed input image. In the feature classification, Mahalanobis distance is used as a measure of the similarity between the feature of an input image and the representative feature of each class. Experimental results for real ultrasound images show that the proposed algorithm yields the improvement of maximum 30% recognition rate than the recognition algorithm using power spectrum and Euclidean distance, and results in better recognition rate of 10-40% than the recognition algorithm using weighted quefrency complex cepstrum.

본 논문에서는 초음파 영상에서 로그 전력 스펙트럼(log power spectrum)을 이용한 장기 인식 알고리듬을 제시한다. 제안한 알고리듬은 크게 특징추출과 특징분류의 두 단계로 구성된다. 특징추출에서는 이동불변의 성질을 가지는 로그 전력 스펙트럼을 이용하여 전처리를 수행한 입력 영상으로부터 장기 조직의 반향(echo of the tissue) 성분을 추출한다. 특징 분류에서는 마하라노비스(Mahalanobis) 거리를 사용하여 입력영상으로부터 추출한 특징벡터와 각 영상 부류의 평균벡터 사이의 유사도를 측정한다. 실제 초음파 영상에 대한 실험결과는 제안된 알고리듬이 전력 스펙트럼(power spectrum)과 유클리드(Euclid) 거리를 이용한 인식 알고리듬보다 최대 30% 향상된 인식률을, 또 가중 큐프런시(weighted quefrency) 복소 켑스트럼(complex cepstrum)을 이용한 알고리듬보다 10∼40% 향상된 인식률을 보여준다.

Keywords

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